Objectives Systemic lupus erythematosus (SLE) is a chronic autoimmune disease that leads to a variety of negative health outcomes resulting from inflammation in various organ systems. Although treatment continues to advance, fatigue remains one of the most salient, poorly understood and addressed patient complaints. Understanding the mechanisms of fatigue can help guide the development of interventions to improve health outcomes. The aim of this research was to evaluate the contribution of six variables (disease activity, insomnia, depression, stress, pain and physical health) to fatigue in SLE without concomitant fibromyalgia (FM). Methods A total of 116 ethnically diverse, primarily female participants (91%) with SLE, receiving care at university medical centers, completed assessments of disease activity and quality of life outcomes (FACIT-FT, Insomnia Severity Index, Perceived Stress Scale (PSS-4), Pain Inventory, Depression-PHQ-9, and LupusPRO-physical function). All patients met the American College of Rheumatology classification criteria for SLE and did not have a known diagnosis of FM. Multivariate linear and stepwise regression analyses were conducted with fatigue (FACIT-FT) as the dependent variable, and the above six variables as independent variables. Results Mean (SD) age was 39.80 (13.87) years; 50% were African American, 21% Caucasian, 13% Hispanic, 9% Asian and 8% other. Mean (SD) FACIT-FT was 20.09 (12.76). Collectively, these six variables explained 57% of the variance in fatigue. In the multivariate model, depression, stress and pain were significantly and independently associated with fatigue, but not disease activity, sleep or physical health. Stress had the largest effect on fatigue (β 0.77, 95% CI 0.17–1.38, p = 0.01), followed by depression (β 0.66, 95% CI 0.21–1.10, p = 0.005). On stepwise regression analysis, only stress, depression and pain were retained in the model, and collectively explained 56% of the variance in fatigue. All three remained independent correlates of fatigue, with the largest contribution being stress (β 0.84, 95% CI 0.27–1.42, p = 0.005), followed by depression (β 0.79, 95% CI 0.44–1.14, p < 0.001) with fatigue. Conclusion Stress, depression and pain are the largest independent contributors to fatigue among patients with SLE, without concurrent FM. Disease activity, sleep and physical health were not associated with fatigue. The evaluation of stress, depression and pain needs to be incorporated during assessments and clinical trials of individuals with SLE, especially within fatigue. This stress-depression-fatigue model requires further validation in longitudinal studies and clinical trials. Significance and innovation: • Disease activity, sleep, pain, stress, depression, and physical health have been reported individually to be associated with fatigue in lupus. This analysis evaluated the role of each and all of these six variables collectively in fatigue among patients with SLE without a known diagnosis of FM. • Disease activity, sleep and physical health were n...

Even after controlling for disease activity and perceived stress, the relationship between pain and CD was explained by sleep disturbance and depression symptoms. Although these relationships need validation in longitudinal studies with additional measurement modalities, our findings may indicate promising, non-pharmacologic intervention avenues for SLE patients with pain and CD. Specifically, cognitive-behavioral therapies for depression and sleep are known to reduce distress and enhance functioning across various psychosocial domains. Given the symptom burden of SLE, interventions that maximize potential benefits without additional pharmacologic treatments may be of particular utility. This article is protected by copyright. All rights reserved.

Objectives LupusPRO has shown good measurement properties as a disease-specific patient-reported outcome tool in systemic lupus erythematosus (SLE). For the purpose of clinical trials, the version 1.7 (v1.7) domain of Pain-Vitality was separated into distinct Pain, Vitality and Sleep domains in v1.8, and the psychometric properties examined. Methods A total of 131 consecutive SLE patients were self-administered surveys assessing fatigue (FACIT, SF-36), pain (Pain Inventory, SF-36), insomnia (Insomnia Severity Index), emotional health (PHQ-9, SF-36) and quality of life (SF-36, LupusPRO) at routine care visits. Internal consistency reliability (ICR) for each domain was obtained using Cronbach's alpha. The convergent construct validity of LupusPRO domains with corresponding SF-36 domains or tools were tested using Spearman correlation. Varimax rotations were conducted to assess factor structures of the LupusPRO v1.8. Results Mean (SD) age was 40.04 (14.10) years. Scores from the LupusPRO-Sleep domain strongly correlated with insomnia scores, while LupusPRO-Vitality correlated strongly with fatigue (FACIT) and SF-36 vitality. The LupusPRO-Pain domain correlated strongly with pain (SF36 Bodily-Pain, Pain Inventory) scores. Similarly, the LupusPRO domains of Physical and Emotional Health had significant correlations with corresponding SF-36 domains. The ICR for HRQoL and non-HRQoL were 0.96 and 0.81. LupusPRO (domains HRQoL and QoL) scores correlated with disease activity. Principal component analysis included seven factor loadings presenting for the HRQOL subscales (combined Sleep, Vitality, and Pain), and three factors for the NHRQoL (Combined Coping and Social Support). Conclusions LupusPRO v1.8 (including its Sleep, Vitality, and Pain domains) has acceptable reliability and validity. Use of LupusPRO as an outcome measure in clinical trials would facilitate responsiveness assessment.

Patients with systemic lupus erythematosus (SLE) frequently experience poor body image (BI), an important issue, though not well researched or understood thus far. BI is perception of one's own body. The effects of disease activity, damage, sleep, stress, pain, fatigue, function, medications, depression and fibromyalgia (FM) on BI in SLE are not known. Objective: We aimed to evaluate the relative role of the specific variables listed above on BI in SLE patients. Methods: SLE patients receiving rheumatology care at two academic medical centers were recruited. Each patient completed questionnaire assessments evaluating target variables and BI. Disease activity was evaluated using SELENA-SLEDAI. Multivariate regression analyses including stepwise modeling were conducted with BI as the dependent variable for all patients and for patients with and without FM. Results: 115 SLE patients participated. Mean (SD) age was 40.1 (13.8) years. For all patients and patients without FM, depression (β-1.7, p 0.02), stress (β-1.8, p 0.05), ACR malar rash (β-13.5, p 0.03), and steroid dose (β-0.4, p 0.04) were found to be independent predictors of BI, and explained 54% of BI variance. On stepwise regression modelling, scores for depression (β-2.2, p <0.001), stress (β-1.6, p 0.05), and disease activity (β-1.5, p 0.005) were found to be predictive of poor BI in the whole group, and similar results were noted among those without fibromyalgia. Malar rash presence as defined in the ACR classification criteria for SLE (β-10.3, p 0.04) was most predictive of poor BI among patients without fibromyalgia. Of the modifiable variables among those without FM, depression and stress had similar contributions to BI, followed by disease activity. In patients with fibromyalgia, depression (β-3.6, p 0.002) alone was associated with BI. Conclusions: Depression, stress, and disease activity are important predictors of BI in SLE patients. Malar rash is a risk for poor BI among those without FM. Attention to depression and stress concurrently with control of disease is suggested among SLE patients with poor BI.

BackgroundA physician global estimate of patient status (DOCGL) was developed to quantify inflammatory activity in rheumatoid arthritis (RA) clinical trials. However, DOCGL may be affected by joint damage and/or distress (in fibromyalgia, depression, etc). One approach to document the possible impact of these problems on DOCGL is to add 3 physician visual analog subscale (VAS) estimates for inflammation, damage, and distress. These subscales have been shown to be useful in patients with diagnoses other than RA (1) but inter-rater reliability has not been analyzed.ObjectivesTo analyze inter-rater reliability between senior rheumatologists and trainees on 4 VAS estimates for overall DOCGL, inflammation (DOCINF), damage (DOCDAM) and distress (DOCSTR), in patients with various rheumatic diagnoses.MethodsPatients seen in routine care were assigned 4 physician VAS estimates for overall DOCGL, and levels of inflammation or reversible symptoms (DOCINF), organ damage or irreversible symptoms (DOCDAM), and distress or symptoms not explained by inflammation or damage (DOCSTR). VAS estimates were assigned independently by a senior rheumatologist and a rheumatology trainee for the same patient at the same visit. Mean differences, correlations, and possible discordance of ≥2units/10 between estimates of the senior rheumatologist and the trainee were analyzed.ResultsVAS estimates by the 2 physicians were analyzed in 64 patients with different rheumatic diseases, including osteoarthritis (16%), RA (14%), fibromyalgia (14%), and systemic lupus erythematosus (13%). Mean differences of scores assigned by the senior rheumatologists versus trainees were <0.43/10, less than 5% of the total scales, slightly lower for DOCINF, and slightly higher for the 3 other subscales (p<0.001) (Table). Mean estimates of both physicians for damage and distress were higher than for inflammation by 1.1 to 1.6 units (Table). Correlations of all 4 VAS between rheumatologists and trainees were significant (p<0.001) (Table). More than 70% of the estimates were concordant for DOCGL (75%), DOCINF (78%), and DOCDAM (70%), while concordance was somewhat lower for DOCSTR (57%) (Table).Table 1.Mean and SD for the four physician estimates according to the rheumatologist (rheum) and the trainee, inter-rater reliability and levels of concordance and discordance for each estimateVAS (0–10)RheumTraineeMean DifferencePearson r, all p<0.001Rheumatologist (Rheum) and trainee discordance groups by 2/10 units, no. (%) Rheum > TraineeRheum = TraineeRheum < Trainee Overall DOCGL3.9 (1.9)4.0 (2.2)-0.05 (1.9)0.6111 (17%)48 (75%)5 (8%)DOCINF1.7 (1.6)1.4 (1.6)0.28 (1.6)0.508 (13%)50 (78%)6 (9%)DOCDAM2.8 (2.2)2.7 (2.2)0.01 (2.0)0.6111 (17%)45 (70%)8 (12%)DOCSTR3.3 (2.9)2.9 (2.4)0.43 (2.8)0.4712 (19%)36 (57%)15 (24%)ConclusionsGood inter-rater agreement between two physicians is seen for 4 VAS estimates for overall global assessment, inflammation, damage, and distress. Mean scores for damage and distress were higher than for inflammation, indicating the complexity of rheumatolog...